From fdd1bdcbe113c568dbeef4de6b9a5ad3c9652ef8 Mon Sep 17 00:00:00 2001 From: TAMARA JERINIC Date: Sat, 16 Apr 2022 19:42:35 +0200 Subject: Dodat zahtev za čuvanje h5 fajla treniranog modela. MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- backend/microservice/api/controller.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) (limited to 'backend/microservice/api/controller.py') diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py index d7564b70..d2b8ed2c 100644 --- a/backend/microservice/api/controller.py +++ b/backend/microservice/api/controller.py @@ -1,3 +1,4 @@ +from gc import callbacks import flask from flask import request, jsonify import newmlservice @@ -27,14 +28,25 @@ class train_callback(tf.keras.callbacks.Callback): @app.route('/train', methods = ['POST']) def train(): print("******************************TRAIN*************************************************") + f = request.files.get("file") data = pd.read_csv(f) paramsModel = json.loads(request.form["model"]) paramsExperiment = json.loads(request.form["experiment"]) paramsDataset = json.loads(request.form["dataset"]) #dataset, paramsModel, paramsExperiment, callback) - result = newmlservice.train(data, paramsModel, paramsExperiment, paramsDataset, train_callback) + filepath,result = newmlservice.train(data, paramsModel, paramsExperiment,paramsDataset, train_callback) + """ + f = request.json['filepath'] + dataset = pd.read_csv(f) + filepath,result=newmlservice.train(dataset,request.json['model'],train_callback) print(result) + """ + + url = config.api_url + "/file/h5" + files = {'file': open(filepath, 'rb')} + r=requests.post(url, files=files) + fileId=r.text return jsonify(result) @app.route('/predict', methods = ['POST']) -- cgit v1.2.3